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hbertv2-Massive-intent

This model is a fine-tuned version of gokuls/bert_12_layer_model_v2_complete_training_new on the massive dataset. It achieves the following results on the evaluation set:

  • Loss: 0.9457
  • Accuracy: 0.8515

Model description

More information needed

Intended uses & limitations

More information needed

Training and evaluation data

More information needed

Training procedure

Training hyperparameters

The following hyperparameters were used during training:

  • learning_rate: 5e-05
  • train_batch_size: 64
  • eval_batch_size: 64
  • seed: 33
  • distributed_type: multi-GPU
  • optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
  • lr_scheduler_type: linear
  • num_epochs: 15

Training results

Training Loss Epoch Step Validation Loss Accuracy
2.1277 1.0 180 1.0263 0.7364
0.9042 2.0 360 0.8013 0.7875
0.6379 3.0 540 0.8182 0.7914
0.4865 4.0 720 0.8074 0.7973
0.3637 5.0 900 0.7780 0.8190
0.3019 6.0 1080 0.7656 0.8288
0.2218 7.0 1260 0.8253 0.8254
0.1741 8.0 1440 0.8295 0.8239
0.1316 9.0 1620 0.8590 0.8308
0.1011 10.0 1800 0.8465 0.8431
0.078 11.0 1980 0.9007 0.8401
0.0573 12.0 2160 0.9133 0.8470
0.0382 13.0 2340 0.9233 0.8470
0.0247 14.0 2520 0.9365 0.8490
0.0148 15.0 2700 0.9457 0.8515

Framework versions

  • Transformers 4.30.2
  • Pytorch 1.14.0a0+410ce96
  • Datasets 2.13.0
  • Tokenizers 0.13.3
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Evaluation results